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Data supporting: "MR Fingerprinting Repeatability in the Brain"


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Authors

Buonincontri, Guido 
Biagi, Laura 
Retico, Alessandra 

Description

This dataset accompanies the journal article, "Multi-site repeatability and reproducibility of MR fingerprinting of the healthy brain at 1.5 and 3.0 T", published at NeuroImage at https://www.sciencedirect.com/science/article/pii/S1053811919302393?via%3Dihub

MRI Fingerprinting is a new method for obtaining MRI data, which obtains quantitative data faster than most clinical techniques. It relies on an MRI acquisition with a pseudorandom pattern, which pseudorandom pattern is simulated with MRI parameters. The acquisition then has a best fit approach to the MRI simulation to result in quantitative parameter maps. The importance of these maps, M0, T1, and T2, is that they are properties that indicate tissue and are expected to change in most disease states. Being able to repeat the measurements on several systems is important if the method is to be useful clinically.

This contains 3D datasets of normal human volunteer brains. The same ten subjects were imaged on 5 MRI scanners at 1.5 T and 3.0 T field strengths. Each subject was imaged with MR Fingerprinting, removed from the scanner, and then re-entered the scanner for a repeated imaging session.

This data is fully anonymous and obtained with the consent of the healthy individuals.

Version

Software / Usage instructions

The data is in a NIFTI format.

Keywords

MRI

Publisher

Sponsorship
Cancer Research Uk (None)
This work was supported by Cancer Research UK, INFN CSN5, from the European Commission (Grant Agreement Number 656937) and the Royal Society. JK acknowledges support by GlaxoSmithKline. FR and FZ receive support from the Engineering and Physical Sciences Research Council and Cancer Research UK. The project was also supported by the Addenbrooke’s Charitable Trust (ACT) and the NIHR Cambridge Biomedical Research Centre ( BRC) award to Cambridge University Hospitals (CUH) NHS Foundation Trust in partnership with the University of Cambridge.
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